This system utilises multi-agent collaboration to automatically source and check content from the web and generate cloze (fill-in-the-blank) tests, publishing them with learning management systems (LMS). It employs a multi-agent workflow in which one agent handles...
This solution analyses photos of handwritten Chinese compositions to provide scores and feedback based on teacher-configurable rubrics. The technical core combines Optical Character Recognition (OCR) with LLMs for text extraction. A multi-agent system separates...
This initiative integrates Agentic AI with a quadruped robot dog to create a hands-on STEM learning experience, allowing students to apply abstract concepts in a physical environment. The solution integrates Agentic AI for autonomous decision-making using LLM-based...
This agent addresses information overload by transforming the student handbook into an interactive dialogue interface. Instead of manually searching through dense documents, students can access essential information and receive clear, conversational explanations of...
Developed by undergraduate students at EdUHK, this platform features a suite of self-learning agents designed to simulate realistic dialogue scenarios. These agents adopt specific personas—such as a rigorous job interviewer, a supportive peer friend, or a technical...
This is a multi-agent system designed to generate personalized lesson plans collaboratively with teachers. It operates with a "human-in-the-loop" mechanism, allowing teachers to review and provide feedback which the system uses to reflect and modify the output. The...